holdouts-generator 0.0.12

Simple python package to generate and cache both random and chromosomal holdouts with arbitrary depth.

Simple python package to generate and cache both random and chromosomal holdouts with arbitrary depth.

How do I install this package?

As usual, just download it using pip:

pip install holdouts_generator

Tests Coverage

Since some software handling coverages sometime get slightly different results, here’s three of them:

Generating random holdouts

Suppose you want to generate 3 layers of holdouts, respectively with 0.3, 0.2 and 0.1 as test size and 5, 3 and 2 as quantity:

from holdouts_generator import holdouts_generator, random_holdouts
dataset = pd.read_csv("path/to/my/dataset.csv")
generator = holdouts_generator(
    dataset,
    holdouts=random_holdouts(
        [0.3, 0.2, 0.1],
        [5, 3, 2]
    ),
    cache=False, # Set this parameter to True to enable automatic caching
    memory_cache=False, # Set this parameter to True to enable automatic in memory caching, usefull when you would reload the objects multiple times
    cache_dir=".holdouts" # This is the default cache directory
)

for (training, testing), inner_holdouts in generator():
    for (inner_train, inner_test), small_holdouts in inner_holdouts():
        for (small_train, small_test), _ in small_holdouts():
            #do what you need :)

Generating chromosomal holdouts

Suppose you want to generate 2 layers of holdouts, two outer ones with chromosomes 17 and 18 and 3 inner ones, with chromosomes 17/18, 20 and 21:

from holdouts_generator import holdouts_generator, chromosomal_holdouts
dataset = pd.read_csv("path/to/my/genomic_dataset.csv")
generator = holdouts_generator(
    dataset,
    holdouts=chromosomal_holdouts([
        ([17], [([18], None), ([20], None), ([21], None)])
        ([18], [([17], None), ([20], None), ([21], None)])
    ]),
    cache=False, # Set this parameter to True to enable automatic caching
    memory_cache=False, # Set this parameter to True to enable automatic in memory caching, usefull when you would reload the objects multiple times
    cache_dir=".holdouts" # This is the default cache directory
)

for (training, testing), inner_holdouts in generator():
    for (inner_train, inner_test), _ in inner_holdouts():
        #do what you need :)

Clearing the holdouts cache

Just run the method clear_cache:

from holdouts_generator import clear_cache

clear_cache(
    cache_dir=".holdouts" # This is the default cache directory
)

Clearing the holdouts memory cache

Just run the method clear_memory_cache:

from holdouts_generator import clear_memory_cache

clear_memory_cache(
    cache_dir=".holdouts" # This is the default cache directory
)